Study
Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction
Study ID | Alternative Stable ID | Type |
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EGAS00001002073 | Other |
Study Description
The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and ... (Show More)
Study Datasets 1 dataset.
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
Dataset ID | Description | Technology | Samples |
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EGAD00001002735 |
mRNA, total RNA, small noncoding RNA, NOMe-Seq and DNase-Seq data from following samples (not every Sequencing Type for every sample):
01_HepG2_LiHG_Ct1
41_Hf01_LiHe_Ct
41_Hf02_LiHe_Ct
41_Hf03_LiHe_Ct
51_Hf03_BlCM_Ct
51_Hf04_BlCM_Ct
51_Hf03_BlEM_Ct
51_Hf04_BlEM_Ct
51_Hf03_BlTN_Ct
51_Hf04_BlTN_Ct
Metadata available at deep.dkfz.de
|
Illumina HiSeq 2000,Illumina HiSeq 2500 | 10 |
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